Abstract

Stochastic simulation of lithology is critical in geological modeling, and the result quality relies on the well data analysis. The traditional method may involve too many uncertainties due to the limited wells. This paper introduces a new method to improve the simulation of lithology distribution of tide-dominated estuary using probability volume generated by stratigraphic forward modeling as key input for trend model. Based on the core analysis and investigation on regional geology, the stratigraphic forward modeling approach generates an initial model by using the sequence stratigraphic scheme. And the sensitivity analysis provides an indication of adjusting the influencing parameters which control the sand and shale distribution. The models will be compared with the well data, geological concept, and seismic attribute. The selected model will be resampled into geological grid to generate the trend volume combined with seismic inversion data. Further, the lithology distribution can be simulated by using stochastic method with the trend volume. This approach has been successfully applied in JE-AW oil field to improve the geological model of M1. Typical tidal sedimentary structures, such as mud drapes, and wavy bedding shown in core and overall upward fining shown in logs, reveal the tide-dominated estuary environment during the deposition of M1. Three sub-zones (layers) of M1 are identified and correlated. Based on the sensitivity analysis, the sediment input and subsidence is adjusted for reliable stratigraphic forward modeling. The trend model is generated by inputting the result from stratigraphic forward modeling and seismic inversion. Finally, the lithology distribution is simulated using the trend model. This method improves the lithology stochastic simulation of tide-dominated estuary honoring the well and seismic data. This method reduces the uncertainties of stochastic modeling caused by limited wells and improves the predictability of lithology model.

Keywords

This paper was prepared for presentation at the 2017 International Field Exploration and Development Conference in Chengdu, China, 21–22 September 2017.

This paper was selected for presentation by the IFEDC&IPPTC Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the IFEDC&IPPTC Committee and are subject to correction by the author(s). The material does not necessarily reflect any position of the IFEDC&IPPTC Committee, its members. Papers presented at the Conference are subject to publication review by Professional Committee of Petroleum Engineering of Shaanxi Petroleum Society. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of Shaanxi Petroleum Society is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of IFEDC&IPPTC. Contact email: paper@ifedc.org or paper@ipptc.org.

Notes

Acknowledgements

We would like to thank Yin Xiangdong, Yang Jinxiu, and Tang Mingming (China University of Petroleum, Huadong) for supporting the stratigraphic forward modeling and sedimentary analysis. They also provide very useful suggestions for the improvement of this paper.